Implements commonly used Indian farm cost concepts for agricultural economic analysis, including Cost A1, A2, B1, B2, C1, C2, and C3. Tools are provided to calculate cost concepts from farm-level input data, aggregate costs across groups, summarize distributions, compute returns and benefit-cost ratios, estimate cost of production and break-even values, decompose cost shares, conduct one-way sensitivity analysis, and visualize concept-wise costs. The implementation is designed for reproducible farm management and cost-of-cultivation studies.
IndFarmCost is an R package for calculating and analysing the Indian farm
cost concepts A1, A2, B1, B2, C1, C2, and C3 used in agricultural
cost-of-cultivation and farm management studies.
| Concept | Formula implemented |
|---|---|
| A1 | Sum of specified A1 cost components |
| A2 | A1 + rent paid for leased-in land |
| B1 | A1 + interest on owned fixed capital excluding land |
| B2 | B1 + rental value of owned land + rent paid for leased-in land |
| C1 | B1 + imputed value of family labour |
| C2 | B2 + imputed value of family labour |
| C3 | C2 + managerial charge; default is 10% of C2 |
The managerial rate is configurable through managerial_rate.
farm_costs() - calculate A1 to C3 for each farm/observation.farm_costs_aggregate() - aggregate cost concepts by crop, state, farm size,
or other grouping variables.summarize_costs() - descriptive statistics and coefficient of variation.farm_returns() - gross return, net returns, and benefit-cost ratios.cost_of_production() - unit cost under a selected cost concept.break_even_price() and break_even_yield() - break-even analysis.cost_shares() - additive cost decomposition and percentage shares.cost_sensitivity() - one-way sensitivity analysis for an input cost.plot.farmcost() - base-R concept-wise cost plot.farm_cost_example() - ready-to-use example farm dataset.install.packages("IndFarmCost_0.1.0.tar.gz", repos = NULL, type = "source")
library(IndFarmCost)
dat <- farm_cost_example()
costs <- farm_costs(dat)
costs[, c("farm_id", "crop", "A1", "A2", "B1", "B2", "C1", "C2", "C3")]
summary(costs)
plot(costs, row = 1)
farm_returns(
costs,
main_output = "main_output_q",
main_price = "main_price_rs_q",
byproduct_output = "byproduct_output_q",
byproduct_price = "byproduct_price_rs_q"
)
The package follows the standard structure of Indian cost concepts used in cost-of-cultivation studies. Users should verify the valuation rules, wage imputation, rental valuation, interest rates, and any study-specific treatment of inputs against the methodology applicable to their dataset and reference period.